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Genetics of mammalian meiosis
Published in C. Yan Cheng, Spermatogenesis, 2018
In addition to SC proteins, cohesins are essential components of the axial/lateral elements. The cohesin complex is required for sister chromatid cohesion in both mitosis and meiosis. The mammalian mitotic cohesin complex consists of two structural maintenance of chromosome (SMC) proteins (SMC1 and SMC3) and two non-SMC subunits (RAD21 and STAG1 or STAG2). Four meiosis-specific paralogues of mitotic cohesins have been identified in mammals: REC8,5,38 RAD21L,39–41 SMC1B,42 and STAG3.43 REC8 and RAD21L are homologous to RAD21. SMC1B bears sequence similarity with SMC1. STAG3 replaces STAG1/STAG2 in meiotic cohesin complexes. All these meiosis-specific cohesin proteins localize to the axial elements. Strikingly, absence of REC8 leads to synapsis between sister chromatids, suggesting that one of the main functions of REC8 is to limit synapsis to homologous chromosomes.38,44 Genetic and cell biological analyses have shown that these meiosis-specific cohesins regulate the axial element formation, axis length, sister chromatid cohesion, and meiotic recombination.45,46
The role of S.aureus and L.plantarum as an immunomodulator of IFNα macrophages and fibronectin dermal fibroblast secretion
Published in Robert Hofstra, Noriyuki Koibuchi, Suthat Fucharoen, Advances in Biomolecular Medicine, 2017
R.S.P. Saktiadi, S. Sudigdoadi, T.H. Madjid, E. Sutedja, R.D. Juansah, T.P. Wikayani, N. Qomarilla, T.Y. Siswanti
Fibronectin. The highest increase of fibronectin levels due to SA exposure was at the highest dosage, SA3. It was probably because S.aureus colonization increased the presentation of antigen by macrophage cells which in turn promoted proinflammation cytokines like IL4 and anti-inflammatory cytokine like TGFβ due to high dosages of pathogens (108 cells/dL). Both IL4 and TGFβ have some extensive function to fibroblast cells, i.e., to promote fibronectin synthesis. (Williams et al. 2001).
Non-technical skills for surgeons: The NOTSS behaviour marker system
Published in Rhona Flin, George G. Youngson, Steven Yule, Enhancing Surgical Performance, 2015
Situation awareness is arguably the most critical non-technical skill, and it is required for accurate decision making, timely communication and appropriate leadership. Situation awareness in NOTSS is defined as ‘developing and maintaining a dynamic awareness of the situation in the operating room, based on assembling data from the environment (patient, team, time, displays, equipment); understanding what they mean, and thinking ahead about what may happen next’. According to Endsley’s model,65 situation awareness comprises of three distinct levels (these are called elements in NOTSS, so that is the terminology used here): element 1, gathering information; element 2, interpreting the information (based on experience); and element 3, projecting and anticipating future states based on this interpretation. Chapter 4 outlines the psychological basis of situation awareness and its relevance to intraoperative surgery: SA1 – Gathering information: Information coming in (to the surgeon) does so from a number of sources including the patient (anatomy), colleagues (verbal and non-verbal cues) and instruments (patient monitors). One of the challenges of surgery in the era of inter-professional teams is for the surgeon to monitor information sources and decide which are important to pay attention to. It is very common for the surgeon to be concentrating so intensely on the current operation that important information is either not seen or heard. This makes successful performance of SA element 2 almost impossible.SA2 – Understanding information: The surgeon needs not only to receive all the information but also to understand its significance. This will of course require a degree of training and experience, so junior surgeons, not being aware of the significance of certain facts, will respond (or not respond) differently than senior, more experienced surgeons. A common problem in correctly interpreting information is something called ‘confirmation bias’. In this instance, information coming in is filtered to allow the surgeon to confirm his or her views, while any information that might suggest another cause is erroneously discarded.SA3 – Projecting and anticipating future state: Having received and (hopefully) recognized the importance of the information, the surgeon must then anticipate potential future events. Experts spend a lot of time thinking about the future and running mental simulations about what may happen as a result of different courses of future action. This may or may not require a change of plan. Problems with incorrect anticipation may be avoided by discussing options with colleagues and reviewing alternatives. This is all a dynamic situation and will change as the operation progresses.
Regional variation in prevalence of difficult-to-treat asthma and oral corticosteroid use for patients in Australia: heat map analysis
Published in Journal of Asthma, 2023
Peter A. B. Wark, Mark Hew, Yang Xu, Clare Ghisla, Tra-My Nguyen, Bora Erdemli, Aditya Samant, Cassandra Nan
Regional asthma prevalence was determined by matching individual patient data to the patient’s postcode and organizing pharmacy prescription claims data into Statistical Area Level 3 (SA3) geographic areas defined by the Australian Bureau of Statistics (23). Each SA3 has a population between 30 000 and 130 000 people, can contain multiple postcodes, and ranges from small clusters of heavily populated communities in or around urban centers to remote areas. This analysis used 340 SA3s, excluding those defined as special-purpose, nonspatial areas. SA3-level data were used to produce heat maps to display four color-coded prevalence ranges of difficult-to-treat asthma, uncontrolled difficult-to-treat asthma, and/or cumulative OCS use throughout Australia. Only nonzero values are shown, and prevalence ranges for each color code were selected for approximate normal distributions for each map. Patients with missing postcode data (6% of the sample) were excluded from the regional analyses.
Efficacy of emicizumab prophylaxis versus factor VIII prophylaxis for treatment of hemophilia A without inhibitors: network meta-analysis and sub-group analyses of the intra-patient comparison of the HAVEN 3 trial
Published in Current Medical Research and Opinion, 2019
Adriana Reyes, Cédric Révil, Markus Niggli, Sammy Chebon, Simone Schlagmüller, Jan-Paul Flacke, Max Zortel, Ido Paz-Priel, Elina Asikanius, Roger Hampton, Anadi Mahajan, Elvira Schmidt, Susan C. Edwards
The SLR identified 94 studies of patients with hemophilia A without inhibitors (Supplementary Figure S1). Of these, three studies of FVIII (prophylactic and on-demand) were eligible for inclusion in the base-case NMA, in addition to the HAVEN 3 trial, which evaluated FVIII prophylaxis and emicizumab prophylaxis. The HAVEN 3 trial contributed its randomized treatment arms to the base-case NMA; data from the NIS that took place prior to HAVEN 3 were not included. Overall, there were four studies in the base-case NMA. From the SLR, one additional study of FVIII prophylaxis was eligible for SA3, which allowed inclusion of non-randomized studies (Supplementary Figure S2). Study characteristics for all five included studies are provided in Table 1, with additional details of outcome (bleed definition) provided in Supplementary Table S7. Details of excluded studies are provided in Supplementary Appendix 4 and Table S8.
Identification of the first homozygous POLG mutation causing non-syndromic ovarian dysfunction
Published in Climacteric, 2018
B. Chen, L. Li, J. Wang, Y. Zhou, J. Zhu, T. Li, H. Pan, B. Liu, Y. Cao, B. Wang
Human ovarian dysfunction comprises a variety of different conditions that each result in irregular menstrual cycles, ovarian failure, and female infertility. Amenorrhea and irregular menstrual cycles are two main features of ovarian dysfunction. Genetic defects can cause ovarian dysfunction, including chromosomal abnormalities and single gene alterations1–7. Mutations in STAG3, BMP15, FSHR, GDF9, NOBOX, MCM8, MCM9, NUP107, MSH4, CSB-PGBD3 and MSH5 can cause recessive primary amenorrhea8–17 or secondary amenorrhea18–20. Sequence variants in POLG, NR5A1, KHDRBS1, and NOBOX are reported to be associated with dominant primary21 or secondary amenorrhea22–24. In our clinical practice, some patients exhibit irregular menstrual cycles and poor outcomes of in vitro fertilization, but there is a lack of knowledge of the potential genetic contribution to this ovarian dysfunction.